Who Cited It

DeepFool: A Simple and Accurate Method to Fool Deep Neural Networks

2016 · 5,392 citations · 11 from inside this corpus

Seyed-Mohsen Moosavi-Dezfooli, Alhussein Fawzi, Pascal Frossard

The source holds an abstract for this work, but its best open-access copy is under cc-by-nc-nd, which does not permit us to republish the text. Read it at the source below.

DeepFool: A Simple and Accurate Method to Fool Deep Neural Networks (2016)DeepFool: A Simple and Accura…Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Fou… (2012)Deep Neural Networks for Acou…Explaining and Harnessing Adversarial Examples (2014)Explaining and Harnessing Adv…Intriguing properties of neural networks (2013)Intriguing properties of neur…Explainable AI: A Review of Machine Learning Interpretability Methods (2020)Explainable AI: A Review of M…Universal Adversarial Perturbations (2017)Universal Adversarial Perturb…Robust Physical-World Attacks on Deep Learning Visual Classification (2018)Robust Physical-World Attacks…Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey (2018)Threat of Adversarial Attacks…Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks (2018)Feature Squeezing: Detecting …Adversarial Examples: Attacks and Defenses for Deep Learning (2019)Adversarial Examples: Attacks…ZOO (2017)ZOOOne Pixel Attack for Fooling Deep Neural Networks (2019)One Pixel Attack for Fooling …Towards Deep Learning Models Resistant to Adversarial Attacks (2017)Towards Deep Learning Models …Adversarial Examples Are Not Easily Detected (2017)Adversarial Examples Are Not …Explaining nonlinear classification decisions with deep Taylor decomposition (2016)Explaining nonlinear classifi…
14 of 14 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.
this paper works it cites works citing it node size = global citations · hover for the full title

What this paper cites, inside the corpus

PaperYearCited
Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Fou…201210,399
Explaining and Harnessing Adversarial Examples20148,146
Intriguing properties of neural networks20135,739

What cites it, inside the corpus

PaperYearCited
Explainable AI: A Review of Machine Learning Interpretability Methods20202,907
Universal Adversarial Perturbations20172,744
Robust Physical-World Attacks on Deep Learning Visual Classification20182,154
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey20182,090
Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks20181,882
Adversarial Examples: Attacks and Defenses for Deep Learning20191,786
ZOO20171,779
One Pixel Attack for Fooling Deep Neural Networks20191,715
Towards Deep Learning Models Resistant to Adversarial Attacks20171,536
Adversarial Examples Are Not Easily Detected20171,428
Explaining nonlinear classification decisions with deep Taylor decomposition20161,413

Links

DOI · Open access copy · OpenAlex record

Topics

Adversarial Robustness in Machine LearningComputer Science
Advanced Neural Network ApplicationsComputer Science
Explainable Artificial Intelligence (XAI)Computer Science

Is this record sound?

complete

Nothing in this record contradicts itself and no field we check is missing.

  • supports3 author record(s) attached.
  • supports25 reference(s) recorded.
  • supportsThe DOI's year agrees with the publication year.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:44+00:00.

sha256 648f8491aaceaa34…